This work explores theoretical patterns of reproduction that maximize the production of resting eggs and the long-term fitness of genotypes in cyclical parthenogens. Our focus is on density-dependent reproduction as it influences the consequences of a trade-off between producing amictic daughters – which reproduce parthenogenetically and subitaneously – and producing mictic daughters – which undergo meiosis and bisexual reproduction. Amictic females increase competitive ability and allow the population to achieve a larger size; mictic females directly contribute to population survival through harsh periods by producing resting eggs. Although morphologically indistinguishable, the two types of females differ greatly in their ecological and reproductive roles. What factors underlie the differential allocation of resources to produce amictic and mictic females?
Using a demographic model based on readily accessible parameters we demonstrate the existence of a frequency of mictic females that will maximize the population's long-term fitness. This frequency, termed the optimal mictic ratio, mo, is 1 − (q/b)1/2, where q is the mortality rate and b is the maximum birth rate. Using computer simulation we compared the fitness of a population with this constant mictic ratio with populations having multiple switches from complete parthenogenetic growth to complete allocation in mixis (mictic ratio either 0 or 1). Two important conclusions for optimal mixis in density-dependent growth conditions are: (1) intermediate mictic ratios are optimal, and (2) optimal mictic ratios are higher when habitat conditions are better. Physiological cues responding to differences in birth and death rates are common so that it is possible that populations may adjust their relative rates of mictic and amictic female production in response to environmentally induced changes to the optimum mictic ratio. Our analysis demonstrates that different patterns of mixis are expected in different type of habitats. Since the optimal mictic ratio is sensitive to the effects of a variety of environmental challenges, our model makes possible a new means to evaluate life history evolution in cyclical parthenogens.